Zobrazeno 1 - 10
of 69 111
pro vyhledávání: '"P, Ramesh"'
This work investigates the potential of tailoring Large Language Models (LLMs), specifically GPT3.5 and GPT4, for the domain of chip testing. A key aspect of chip design is functional testing, which relies on testbenches to evaluate the functionality
Externí odkaz:
http://arxiv.org/abs/2406.17132
In current study, we perform the analysis of an extreme ultraviolet (EUV) wave on 2022 March 31. The event originated from the from NOAA active region (AR) 12975 (location: N13W52) in the Atmospheric imaging Assembly (AIA) onboard Solar Dynamics Obse
Externí odkaz:
http://arxiv.org/abs/2407.03281
The rapid adoption of machine learning (ML) has underscored the importance of serving ML models with high throughput and resource efficiency. Traditional approaches to managing increasing query demands have predominantly focused on hardware scaling,
Externí odkaz:
http://arxiv.org/abs/2407.03583
Autor:
Ramesh, Anirudh, Reilly, Daniel R., Lee, Kim Fook, Moraw, Paul M., Chung, Joaquin, Islam, Md Shariful, Peña, Cristián, Han, Xu, Kettimuthu, Rajkumar, Kumar, Prem, Kanter, Gregory
Interference between independently generated photons is a key step towards distributing entanglement over long distances, but it requires synchronization between the distantly-located photon sources. Synchronizing the clocks of such photon sources us
Externí odkaz:
http://arxiv.org/abs/2407.01225
We apply a recently developed first-principles based approach for treating generic spin-phonon couplings in materials with strong spin-orbit coupling to study $\alpha$-RuCl$_3$. Of particular focus is the potential for this material to exhibit a phon
Externí odkaz:
http://arxiv.org/abs/2407.00660
Spin-phonon coupling underlies a number of diverse range of phenomena of recent interest, particularly in transition metal insulators with strong spin-orbit effects, where it may give rise to hybrid magnetoelastic excitations, and the controversial p
Externí odkaz:
http://arxiv.org/abs/2407.00659
Autor:
Sau, Ramesh Chandra, Yin, Luowei
Deep learning-based partial differential equation(PDE) solvers have received much attention in the past few years. Methods of this category can solve a wide range of PDEs with high accuracy, typically by transforming the problems into highly nonlinea
Externí odkaz:
http://arxiv.org/abs/2407.00442
Autor:
Seshadri, Rikhil, Siva, Jayant, Bartholomew, Angelica, Goebel, Clara, Wallerstein-King, Gabriel, Morato, Beatriz López, Heller, Nicholas, Scovell, Jason, Campbell, Rebecca, Wood, Andrew, Ozery-Flato, Michal, Barros, Vesna, Gabrani, Maria, Rosen-Zvi, Michal, Tejpaul, Resha, Ramesh, Vidhyalakshmi, Papanikolopoulos, Nikolaos, Regmi, Subodh, Ward, Ryan, Abouassaly, Robert, Campbell, Steven C., Remer, Erick, Weight, Christopher
Kidney cancer is a global health concern, and accurate assessment of patient frailty is crucial for optimizing surgical outcomes. This paper introduces AI Age Discrepancy, a novel metric derived from machine learning analysis of preoperative abdomina
Externí odkaz:
http://arxiv.org/abs/2407.00438
Autor:
Yadav, Lalit, Bag, Rabindranath, Dhakal, Ramesh, Winter, Stephen M., Rau, Jeffrey G., Kolesnikov, Alexander I., Podlesnyak, Andrey A., Brown, Craig M., Butch, Nicholas P., Graf, David, Gingras, Michel J. P., Haravifard, Sara
In this study, a novel material from the rare-earth based breathing pyrochlore family, Ba3Tm2Zn5O11, was successfully synthesized. Powder X-ray diffraction and high-resolution powder neutron diffraction confirmed phase purity and crystal structure, w
Externí odkaz:
http://arxiv.org/abs/2407.00222
We use the GIBLE suite of cosmological zoom-in simulations of Milky Way-like galaxies with additional super-Lagrangian refinement in the circumgalactic medium (CGM) to quantify the origin and evolution of CGM cold gas clouds. The origin of $z$\,$=$\,
Externí odkaz:
http://arxiv.org/abs/2407.00172